AUTHOR=Yang Kai , Tong Li , Shu Jun , Zhuang Ning , Yan Bin , Zeng Ying TITLE=High Gamma Band EEG Closely Related to Emotion: Evidence From Functional Network JOURNAL=Frontiers in Human Neuroscience VOLUME=Volume 14 - 2020 YEAR=2020 URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2020.00089 DOI=10.3389/fnhum.2020.00089 ISSN=1662-5161 ABSTRACT=High frequency electroencephalography (EEG) signals have been playing an important role in researches of human emotions. However, there is not enough clarity about the different network patterns under different emotional states in the high gamma band (50–80 Hz). In this paper, we investigate the different emotional states by using functional network analysis on various frequency bands. We constructed multiple functional networks on different frequency bands and performed functional network analysis and time-frequency analysis on these frequency bands to determine the significant features that represent different emotional states. Furthermore, we verified the effectiveness of these features by using them in emotion recognition. Our experimental results proved that the network connections in the high gamma band with significant differences among the positive, neutral, and negative emotional states were much denser than the network connections in other frequency bands. The connections mainly occurred in the left prefrontal, left temporal, parietal, and occipital regions. Moreover, long-distance connections with significant differences among the emotional states were observed in the high frequency bands, especially the high gamma band. Also, high gamma band fusion features derived from the global efficiency, network connections, and differential entropies achieved the highest classification accuracies for both our dataset and the public dataset. These results are consistent with literature and provide further evidence that high gamma band EEG signals are more sensitive and effective than other frequency bands in human affective perception.